Predictive performance of NMME seasonal forecasts of global precipitation: A spatial-temporal perspective

doi:10.1016/j.jhydrol.2018.12.036

	Predictive performance of NMME seasonal forecasts of global precipitation: A spatial-temporal perspective
	Zhao, Tongtiegang 1; Zhang, Yongyong 2; Chen, Xiaohong 1
刊名	JOURNAL OF HYDROLOGY
	2019-03-01
卷号	570 页码:17-25
关键词	Global climate model Seasonal forecasts Precipitation Anomaly correlation North American Multi-Model Ensemble
ISSN号	0022-1694
DOI	10.1016/j.jhydrol.2018.12.036
通讯作者	Chen, Xiaohong(eescxh@mail.sysu.edu.cn)
英文摘要	Global climate models (GCMs) produce informative seasonal forecasts of global precipitation months ahead of the occurrence for hydrological forecasting. Meanwhile, the skill of GCM forecasts varies by location and initialization time. In this paper, we investigate the anomaly correlation, which indicates the correspondence between forecasts and observations, for 10 sets of global precipitation forecasts in the North American Multi-Model Ensemble (NMME) project. We propose to use principal component analysis to characterize the variation of anomaly correlation. We identify the existence of spatial and temporal patterns at the global scale. The spatial pattern reveals that high (low) anomaly correlation at one initialization time coincides with high (low) anomaly correlation at other initialization times. In other words, for a grid cell, the anomaly correlation at different initialization times tends to be similarly high, or low. It is observed that some of the regions where grid cells are with overall high anomaly correlation tend to exhibit tele-connections with global climate drivers. On the other hand, the temporal pattern suggests that the anomaly correlation tends to improve with initialization time. This pattern is attributable to data assimilation that bases forecasts at a later initialization time on more global observations and simulations. Generally, the two patterns are effective and explain 50% to 70% of the variation of anomaly correlation for the 10 sets of NMME forecasts. The projections of anomaly correlation vectors onto the two patterns help illustrate where and when the NMME precipitation forecasts are skillful.
资助项目	Natural Science Foundation of China (NSFC)[91547202] ; Natural Science Foundation of China (NSFC)[51479216] ; Natural Science Foundation of China (NSFC)[41671024] ; Natural Science Foundation of China (NSFC)[91547108] ; Natural Science Foundation of China (NSFC)[51779279] ; Natural Science Foundation of China (NSFC)[51822908] ; Ministry of Science and Technology of China (MSTC)
WOS关键词	SYSTEM ; MODEL ; TEMPERATURE ; RAINFALL ; SKILL ; ENSO
WOS研究方向	Engineering ; Geology ; Water Resources
语种	英语
出版者	ELSEVIER SCIENCE BV
WOS记录号	WOS:000460709400002
资助机构	Natural Science Foundation of China (NSFC) ; Ministry of Science and Technology of China (MSTC)
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/49233]
专题	中国科学院地理科学与资源研究所
通讯作者	Chen, Xiaohong
作者单位	1.Sun Yat Sen Univ, Ctr Water Resources & Environm, Guangzhou, Guangdong, Peoples R China 2.Chinese Acad Sci, Key Lab Water Cycle & Related Land Surface Proc, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Zhao, Tongtiegang,Zhang, Yongyong,Chen, Xiaohong. Predictive performance of NMME seasonal forecasts of global precipitation: A spatial-temporal perspective[J]. JOURNAL OF HYDROLOGY,2019,570:17-25.
APA	Zhao, Tongtiegang,Zhang, Yongyong,&Chen, Xiaohong.(2019).Predictive performance of NMME seasonal forecasts of global precipitation: A spatial-temporal perspective.JOURNAL OF HYDROLOGY,570,17-25.
MLA	Zhao, Tongtiegang,et al."Predictive performance of NMME seasonal forecasts of global precipitation: A spatial-temporal perspective".JOURNAL OF HYDROLOGY 570(2019):17-25.